class_docstr: Samples elements from [0, length) at fixed intervals.
  
  Parameters
  ----------
  length : int
      Length of the sequence.
  interval : int
      The number of items to skip between two samples.
  rollover : bool, default True
      Whether to start again from the first skipped item after reaching the end.
      If true, this sampler would start again from the first skipped item until all items
      are visited.
      Otherwise, iteration stops when end is reached and skipped items are ignored.
  
  Examples
  --------
  >>> sampler = contrib.data.IntervalSampler(13, interval=3)
  >>> list(sampler)
  [0, 3, 6, 9, 12, 1, 4, 7, 10, 2, 5, 8, 11]
  >>> sampler = contrib.data.IntervalSampler(13, interval=3, rollover=False)
  >>> list(sampler)
  [0, 3, 6, 9, 12]
code: def __iter__(self):
      for i in range(self._interval if self._rollover else 1):
          for j in range(i, self._length, self._interval):
              yield j
  
imports: import numpy
label_desc: Use image node_id 2 for calling the IntervalSampler obj's underlying member method code with example usage: obj.__iter__() without return types